Digital health solutions and integrated COVID-19 and TB services to help recover TB care and prevention services in the COVID-19 pandemic: A descriptive study in four high TB burden countries

Background The measures undertaken to control COVID-19 have disrupted many platforms including tuberculosis (TB) healthcare services. Consequently, declines in TB notifications have been observed in various countries. We visualized changes over time in TB and SARS-CoV-2 infection notifications and reported on country-specific strategies to retain TB care and prevention services in Kyrgyzstan, Nigeria, Tanzania, and Vietnam. Methods We collected and visualized quarterly, retrospective, and country-specific data (Quarter (Q) 1 2018- Q1 2021) on SARS-CoV-2 infection and TB notifications. Additionally, we conducted a country-specific landscape assessment on COVID-19 measures, including lockdowns, operational level strategy of TB care and prevention services, and strategies employed to recover and retain those services. We used negative binomial regression models to assess the association between the installation of COVID-19 measures and changes in TB notifications. Results TB notifications declined in Kyrgyzstan and Vietnam, and (slightly) increased in Nigeria and Tanzania. The changes in TB notifications were associated with the installation of various COVID-19 prevention measures for Kyrgyzstan and Vietnam (declines) and Nigeria (increases). All countries reported reduced TB screening and testing activities. Countries reported the following strategies to retain TB prevention and care services: digital solutions for treatment adherence support, capacity building, and monitor & evaluation activities; adjustment in medication supply/delivery & quantity, including home delivery, pick up points, and month supply; integrated TB/COVID-19 screening & diagnostic platform; and the use of community health care workers. Conclusion Following the COVID-19 pandemic, we did not observe consistent changes in TB notifications across countries. However, all countries reported lower operating levels of TB prevention and care services. Digital health solutions, community-based interventions, and the integration of COVID-19 and TB testing services were employed to recover and retain those services.

2. Please provide additional details regarding participant consent.In the ethics statement in the Methods and online submission information, please ensure that you have specified what type you obtained (for instance, written or verbal, and if verbal, how it was documented and witnessed).If your study included minors, state whether you obtained consent from parents or guardians.If the need for consent was waived by the ethics committee, please include this information.We have adjusted the Ethics statement.However, we stand by our first explanation that ethical review of anonymous surveillance data and a landscape assessment done by project members (which did not include any personal data) do not require approval of an ethics committee and nor a written or verbal informed consent.
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Response to the reviewers:
Reviewer #1: I have read with great interest the study by Spruijt and colleagues regarding the impact of COVID-19 on TB services in four high TB burden countries.The research question is of utmost important and the study provides timely findings, showing the importance of implementing digital tools to counteract the negative consequences of the pandemic on TB prevention and care.The article is well-written but would benefit from revision, with particular focus on the methods.In fact, I believe that a more detailed description of the approaches used to address the study objectives would help interpretation and enable replication/reproducibility.Thank you for this suggestion.We have re-written the methods section and provided a more detailed description of the different approaches used to study the objectives.Most of the study is qualitative in nature, aside from the use of statistical modelling to determine associations between various COVID-19-related measures and TB notification rates.The dual nature of the study, which allowed to provide insights into the reasons behind certain events and measures taken to retain TB activities in spite of the ongoing challenges, could be better emphasized as a strength of the study.Thank you, we have highlighted this strength in the discussion section.
Please see more detailed comments/questions below: Major comments: 1) Abstract: Only three countries are mentioned in the background, but a fourth country (Vietnam) appears in the results, which generates confusion.Also, I think it would be nice to briefly indicate the data sources in the methods, so that readers understand right away whether the study being reported pertains to the national context or specific areas within each country.We have added Viet Nam to the list of countries in the abstract.Furthermore, we added the following sentence to "Study design and setting of the methods section: "We performed a cross sectional study on the impact of COVID-19 IPC measures on national TB notification trends and assessed Nigeria,Tanzania,Viet Nam (1)." [Page X, Lines X-X] 2) Methods, lines 106-108: I wondered whether the authors could elaborate a bit more on the methods used to conduct the landscape assessment.Were TB representatives interviewed or invited to fill out a written questionnaire?We added the following sentence to the methods section -data collection: "The landscape assessment was conducted through an online questionnaire designed in MS Forms."[Page X, lines X-X] 3) Methods, lines 124-125: I am not convinced that using the term "trends" is appropriate here, given that -to my understanding -no statistical analyses were undertaken to examine trends (i.e., trend tests or other approaches).I would lean towards using a less specific terminology, e.g., "change over time".Thank you for this suggestion.We have adjusted the sentence in the methods section and usage of the term "trends" throughout the manuscript.4) Methods, lines 128-130: I think that adding a brief explanation about the reasons for choosing the Eta coefficient would be helpful to the reader (perhaps the non-linear nature of the relationship between variables?).In addition, "correlation" and "association" are not synonyms, so I would not talk about "association" here as the Eta coefficient only reflects correlation.After of reconsideration and comments of the other reviewers.We have decided to remove the presentation of the ETA coefficient in this manuscript as does not add important information (in addition to the IRR form the Negative Binomial Regression model).5) Methods, line 133: While I do understand the need for a negative-binomial model instead of Poisson given the problem of overdispersion, I think the model's description should be expanded a bit to clarify 1) the purpose of this analysis, 2) the model specification (i.e. which variables were included and why/how these were selected), the estimated measures (crude/adjusted incidence rate ratios and 95% CIs?).Thank you for these suggestions.We have adjusted the text into the following: "Third, we assessed the effect of COVID-19 IPC measures being present, including lockdown (yes/no); wearing face masks (yes/no); social distancing (yes/no); limited public transport (yes/no) (independent variables; categorical data) on quarterly reported TB notifications (dependent variable; count data).During exploratory analysis, we detected overdispersion in the data: the variance exceeded the mean and a significant One-Sample Kolmogorov Smirnov Test (Supplement 2).To account for this overdispersion, we employed an univariable negative binomial regression model with log-link functions to estimate crude incidence rate rations with 95% confidence intervals (2)." [Page X, Lines X-X] 6) It remains unclear to me whether and how data on COVID-19 control measures (e.g.lockdowns) were utilized in analysis.Was it possible to account for the variable duration of such measures, the fact that some of these measures may have been introduced and lifted multiple times over the observation period?The COVID-19 IPC measures were included in univariable regression models, in which we assessed the quarterly presence of the IPC measures (dichotomous data -yes/no) with the quarterly change in TB notifications (count data).We added these details to the methods section.[Pages 8, And what about the problem of COVID-19 testing capacity, which may have led to underestimate the number of cases in some countries, possibly affecting the decision-making process concerning anti-COVID-19 public health measures?We are aware that the actual number of COVID-19 cases may be higher than the SARS-CoV-2 notification data is showing.However, we did not study the association between SARS-CoV-2 infection notifications and installment of IPC measures.But we focused on how the installment of the IPC measures were associated with changes in TB notification numbers.We added a description to the discussion section on the limitation of using SARS-CoV-2 notification data.[Pages 18, Relatedly, it would be important to provide the definition of each measure of interest (e.g.lockdown, social distancing, etc) in each country, given that between-country differences exist.We included Table 1 in the manuscript to provide the reader with country-specific definitions of lockdown and social distancing.We added the following sentence to the methods section: "COVID-19 IPC measures consisted of 1) Any type of lockdown; 2) Social distancing; 3) wearing face masks in public spaces; 3) limited availability of public transportation.7) The authors talk about "notified COVID-19 cases", which likely represent the number of those testing positive for SARS-CoV-2 regardless of clinical presentation.Unless there is confidence that such notified cases were symptomatic and can thus be labelled as "COVID-19 cases", I believe that talking about "notified SARS-CoV-2 infections" would be more appropriate.Thank you for this suggestion.We agree that COVID-19 cases refers to number tested positive.Hence, we adjusted the terminology throughout the manuscript.8) Results, lines 147-149: I would suggest reporting in text the average incidence or number of reported cases in each country.Figure 1 is great and very helpful to see how numbers changed over time, but adding numbers in the description of the results would further clarify the magnitude of the problem.Thank you for this suggestion.We have added the numbers representing the increases in SARS-CoV-2 infections to the text [Results section, page 9, lines 196-204] 9) Results, lines 161-168: From this paragraph the reference level is unclear.How did the authors calculate the percent decline at a given timepoint?Was it determined relative to the previous quarter?Or relative to the same quarter of the previous year?Other?I think it is particularly important to clarify this point in part because comparing different quarters would fail to account for the known seasonal variability in TB case detection.We have adjusted the paragraph, and now only reported the highest reported number.[Results section,page 9, 10) Results, lines 225-226: Did these algorithms include the use of integrated testing platforms allowing to detect TB and COVID-19 on the same sample and/or at the same time?Would it be possible to expand a bit on this point and briefly explain how such algorithms were structured?References would also be helpful.We added the following text to the results section: "In Nigeria and Viet Nam,  and TB responses were integrated by adopting an integrated COVID-19/TB screening algorithm for "emergency use approval".The algorithm is currently under consideration to be included in the ational GeneXpert guideline in Nigeria.In Viet Nam, TB screening was integrated into COVID-19 vaccination sites under the USAID Erase TB project."[Results section, page 14, lines 277-281] 11) Discussion, lines 238-241: I would suggest greater caution in interpreting the study findings regarding the impact of different measures on TB notification levels.To my understanding, various potential confounders, including seasonality, were not accounted for in the models.Before making strong claims on the effect of a given measure, it is important to clearly describe how the impact evaluation was carried out, and -in the event that potentially important factors could not be properly considered -discuss the expected implications for the results.As noted above, perhaps this can be adequately addressed by simply describing the model structure more in detail.Thank you for this comment.We have adjusted the methods section and described the model in more detail.Additionally, we adjusted the first paragraph of the discussion section, which now shows "associations" rather than direct impact of COVID-19 IPC measures on TB notifications.

Minor comments:
1) I would suggest checking the paper for minor spelling and grammar errors.We had the paper proof read by a native speaker.
2) In the title, the study country income level should be corrected to "lower-middle income" (instead of "low-middle"), as per World Bank classification system.We have corrected the study country income level to lower-middle income throughout the document.
3) Line 95: Please add a reference to support the statement that the chosen countries have a high TB burden.We have added the following reference to the manuscript: Global tuberculosis report 2021.Geneva: World Health Organization; 2021.Licence: CC BY-NC-SA 3.0 IGO. 4) Line 139: Does "online dataset" corresponds to "publicly available datasets"?If so, I would opt for the latter in the interest of clarity.We have adjusted "online available data / online dataset to publicly available datasets" throughout the manuscript.5) I would suggest removing p-values from text and tables.Reporting 95% CIs is more than enough to capture the uncertainty around model estimates, not to mention that a p-value of 0.00 looks quite strange.Although there were no p-values in the text, we removed the p-values from table 5. 6) Discussion, line 250: I would suggest changing to "decline in healthcare seeking" or (better) "change in healthcare seeking behaviours".We adjusted the text in the manuscript accordingly.

Reviewer #2: Summary
In this study, Spruijt and colleagues described TB case notifications in 4 high TB burden countries, as well as some rates of TB treatment uptake and completion.These trends are graphically illustrated.Data were collected by KNCV country officers.The findings of this study are very interesting and will be valuable to the TB field.However, there are some important shortcomings to the paper, namely with respect to the regression analysis.I don't think it's necessarily the right analysis to assess the effect of IPC measures on TB case notifications.Further elaboration is needed in certain areas.Please see below for specific comments.

Specific comments
Title: Perhaps consider altering title to be "four countries with high TB burdens" instead of referring to income level?Just a thought Thank you for the suggestion, we have adjusted the title.

Abstract:
Background lists 3 countries but the title suggests that 4 countries are included.I think you forgot Vietnam.Thank you for notifying this, we have adjusted the abstract and included Viet Nam in the list of countries.
In Results, I would suggest reporting the notification trends in the order that the countries are named in the background.As it stands, the results jump around a bit and only 3 countries are talked about, which left me wondering about Tanzania's trend.We have included Tanzania in the results section of the abstract.We decided to keep he countries grouped according to the change in their TB notification trends.We adjusted the text into the following: "TB notifications declined in Kyrgyzstan and Viet Nam, and (slightly) increased in Nigeria and Tanzania.The changes in TB notifications were associated with the installation of various COVID-19 prevention measures for Kyrgyzstan (declines) and Nigeria (increases)."[Abstract section, Page 2, Lines 44-53] Also in the Results, it says that "Countries reported the following strategies to retain TB prevention and care services: …" but it is not stated whether these interventions were associated with a change in notifications.We do not have data on when these strategies were implemented.Therefore, we cannot link them to changes in notifications.
Then, the Abstract conclusion states that "Digital health solutions and the integration of COVID-19 and TB testing services have great potential to recover and retain TB care and prevention services", but this has not been substantiated earlier.Please revise for consistency and completeness.Thank you for pointing this out.We have adjusted the conclusion of the abstract into the following: "Following the COVID-19 pandemic, we did not observe consistent changes in TB notifications across countries.However, all countries reported lower operating levels of TB prevention and care services.Digital health solutions, community-based interventions, and the integration of COVID-19 and TB testing services were employed to recover and retain those services."[Abstract section, Pages 2, Lines 54-58]

Methods
Line 114-115: the period stated here is Q1 2018 -Q1 2020, but do you mean Q1 2021?Thank you or detecting this error.We have adjusted the text accordingly.
Line 115-116: what is the "Global Tuberculosis"?Thank you for detecting this error -this should be "Global Tuberculosis Programme": we adjusted the text accordingly.
Line 115-117: Was it not possible to get more granular data from Viet Nam? Assuming a constant rate (i.e., the annual total divided by 4) of TB notifications throughout 2020 seems like an important assumption that could impact the later analyses and erase some important trends.Any comment on this?No unfortunately, we were not able to obtain quarterly data from the National TB Program of Viet Nam.Therefore, we used TB notification data from WHO.However, WHO only has presented quarterly TB notification data from Q1 2020 onwards on their website.Data prior to Q1 2020 is annual data.Indeed, because we might be missing important trends, we did not include Viet Nam in the statistical analysis.
Line 118-121: what countries are we talking about here?Please name in-text.We added the text "for all countries" to the sentence.
Line 124-125: how did you visualize this? i.e.,what software did you use?We used Microsoft Excel for this.We adjusted the text accordingly.
Line 128: what is an ETA coefficient?Some explanation of this measure would be welcome This is a measure for correlation.However, the ETA coefficient is less informative than the final results of the regression model.Therefore, we have deleted the ETA coefficient from this paper.
Line 333: reference 10 needs more detail, I think.I wanted to check what the Pearson scale was but there's no reference to chapter or page number here.Is this the same as 'Pearson's r'?I'm a bit unclear about the analysis; specifically, why the ETA was done and why Pearson's correlation scale was used for interpretation of the prior correlation.After of reconsideration and comments of the other reviewers.We have decided to remove the presentation of the ETA coefficient in this manuscript as does not add important information (in addition to the IRR form the Negative Binomial Regression model).
I think that may be the result of me not understanding the structure of the data, but could you elaborate a bit?Wasn't the negative binomial regression also run to assess the association between COVID-19 IPC measures and TB notifications?That was indeed the case.We have rewritten the methods section, which now accommodates a clearer description of the type of data collected, the type of analysis in regards to their objectives, and what type of data was used in those analysis.We envision that this adjusted methods section now clearly indicates the structure of the data and the objective of doing the binomial regression.
Am I correct in saying that what we're trying to understand here is whether IPC measures had an impact, i.e., a causal effect, on TB notifications within particular countries?The IPC measures were policy interventions applied at a group level.I am not an expert in social epidemiology, but to me it seems that the situation at hand, i.e., repeated within-state measures taken before and after welldefined policy changes, could be appropriately analysed using quasi-experimental modeling.I would strongly recommend consulting with a biostatistician, but I think a fixed effects model (i.e., where each country serves as its own control before IPC measures were implemented and case after IPC measures were implemented, therein controlling confounding to a certain degree) may be appropriate.The textbook Methods in Social Epidemiology 2nd Edition (Oaks and Kaufman) has a good chapter on fixed effects and difference in differences models that will likely be informative, https://pubmed.ncbi.nlm.nih.gov/24366487/ may be as well.
In the statistical analysis of this study, we are assessing whether there is a change in TB notifications that can be associated with the installment of IPC measures.We performed for each country univariable regression analysis (1 per IPC measure).The data that we used as an independent variable is aggregated (quarterly) count data.The appropriate methods for analysis of count data is Poisson regression models or -in case of overdispersion-negative binomial regression models.Our data do not allow for assessing a causal effect, nor do we have individual level data that would allow for fixed effects models.We have adjusted the methods section and incorporated a more detailed description of the data used and type of statistical analysis.

Results
Line 147-151: since there are only 4 countries under consideration, for clarity I think it would be better if you just name the countries at issue instead of saying "all countries except for YYY", since that really only means 2 or 3 countries.We adjusted the text accordingly throughout the manuscript.
Figure 1: Figure 1 contains a lot of information and is still relatively easy to follow.The main suggestion I have would be to try to get the boxes to be easier to discern from each other.Sometimes it is hard to know what box corresponds to each number.Perhaps the box outlines could each be a different colour and the corresponding number could be written in that colour too?As well, I'd suggest changing the numbers for each IPC to be a letter (e.g., a b c d), since there are already so many numbers in the plot Thank you for your suggestions to improve readability of Figure 1.We try to avoid using colors to accommodate persons who are colorblind.We changed the numbers of the IPC measures into letters.We also added the quarterly periods in the legend behind the IPC measures.Line 171-177: so a separate model was run for each IPC measure?That was not very clear from the methods, please update and specify this.Yes, that is indeed what we have done.We have now included a clearer description in the methods section of this analysis.

Table 5 (line 180):
▪ why is this table called Table 5? Why is there another Table 5 on line 232?Please check manuscript over for style consistency!Apologies for this error, we corrected the numbering of the tables.▪ Why is it informative to consider these results in terms of the ETA coefficient instead of just interpreting the IRRs?We calculated the ETA coefficient as pre-analysis to study associations.However, we agree that the ETA coefficient has no added value here and could be removed from the table as the IRR's provide the information of interest.▪ What does the "1" in every cell in the IRR (95% CI) column mean?The one indicates the references category, we have adjusted 1 into REF and included REF in the acronym section.Additionally, we added the 2 categories of the independent variables (yes/no) for clarification.
Line 186: what does "operate at a lower level" mean?To me, level sounds like "level of the healthcare system" i.e., central or peripheral etc.Low capacity? Please clarify in-text.Operational level strategy = the means used by organizations and services to accomplish their overall objectives.We adjusted terminology and added this description to table 3. Furthermore, we adjusted the text into the following: "For Kyrgyzstan, all TB diagnostic and treatment services were reported to operate at a lower operational level (e.g. using less means to accomplish objectives) when compared to pre-pandemic operational levels (  Lines 209-230: again, this is really interesting information but it isn't clear how it was collected and it is not clear if these interventions were implemented across the country or just in select settings.More details are needed to understand if these strategies were deployed throughout countries.This will help readers understand the generalizability of the findings The data of these results were collected through the landscape assessment.The objective of this paper is not to be able to generalize results or interventions to other countries.The paper is descriptive in nature and serves as lessons learned and inspiration from the countries included for other countries.in the methods section of this analysis.
Other Table 5: what do the dark squares indicate?Suggest instead writing 'yes' or 'no'.Acronyms need to be spelled out in the table legend or as a footnote.We adjusted the table accordingly.

Discussion
Lines 235-243: in the results the findings are termed with respect to "association between IPC and change in TB notification', but in the discussion the findings are termed as "the effect of IPC measures".This is an important and substantial difference in statistical terminology.The former may well be correct, but I really don't think with the modeling that's been done in this paper we can talk at all about "the effect of IPC on the outcome" -I don't think the appropriate models have been run to talk about causal effect of IPC on TB case notifications.We agree that the paragraph needs reformulating, we assessed an association and are not able to prove any causal effect.Hence, we reformulated the first paragraph in the discussion section.[Pages X, Lines X-X].
Additionally, no analysis was run that showed that the digital treatment support activities had any effect on TB notifications.The timing of digital interventions may have temporally coincided with rising TB case notifications, but that certainly does not mean that their implementation was the cause behind the notification rise.We apologize for this misunderstanding.We did not associated any digital treatment support activities to changes in TB notifications (we only analyzed the association for IPC measures).However, we indicated and discussed that digital support activities could help to retain and recover lower operating TB services in countries.
Line 245-256: these conclusions are much more reflective of what was actually observed in the study.Thank you.Line 262-265: again, while I agree that the countries did implement these digital etc interventions, and that the aim was to recover and maintain TB prevention and care services, I don't think that this is what the paper has shown.The results of the landscape assessment show that countries followed WHO advice and implemented interventions to retain / recover their TB care and preventions services.Line 270-272: yes agree that this is what the study showed.Thank you.Line 274-275: I think that that is fine!Thank you.
Line 275-287: I agree, the visual depictions are very illustrative.It's better to not stretch data to reach conclusions that the analyses don't necessarily support, and to be conservative in conclusions drawn.
The descriptive data provided here is informative in and of itself and more attention and space should be given to how exactly it was collected, and those findings could be further elaborated upon.We have re-written the methods section to clarify the type of data collected and analyzed in relation to their objectives.Agree with the conclusions stated here.Thank you.

Reviewer #3: Summary:
This study looks at the relation between population-level COVID control measures and TB case ndnotifications to the national TB programs in four high-TB-incidence countries from Q1 2018-Q1 2021, as well qualitative changes in those TB prevention and care programs during the COVID pandemic.
Trends were visualized for all 4 countries.A statistical analysis for correlation between COVID interventions and the number of TB notifications during the intervention period was conducted for 2/4 countries.Changes TB service levels as well as adaptations made by TB programs during the study period are described.
The four study countries all had different experiences during the study period.A wide range of COVID interventions (from none to comprehensive) were documented.Two countries experiences a marked drop in TB notifications during the COVID pandemic; the third had fluctuating notifications and the fourth continued the slow increase observed prior to the COVID pandemic.The statistical analysis found no clear relationship between COVID measures and TB case notifications (strong correlation but in opposite directions for the two countries studied).All countries experienced at least some reductions in TB service levels during the study period, and made extensive adaptations to TB services.

Recommendations:
Language and writing: Major: 1.A thorough copy-edit would help to improve readability and flow -there are many minor grammatical and word choice issues, and it is sometimes hard to follow the sequence of information.As an example, line 38-40 in the abstract reads 'we conducted a country-specific landscape assessment on COVID-19 measures … and employed strategies to recover and retain those services', but I think what the authors mean is '…on COVID-19 measures and strategies employed'.We had an editor check the manuscript for inconsistencies.
2. Re flow -it would help the reader follow along to organize the results under subheadings of Descriptive data (Figure 1, Table 2, and accompanying text) then Statistical analyses (The paragraph on impact of COVID-19 IPC measures on TB notification, and the first Table 5, on line 180).Thank you for this suggestion, we have re-organized the results.
3. Careful copy-editing to check number consistency is also essential to make sure the information is clear.There are multiple occasions where the numbers given are not consistent, making it difficult to know which is correct (eg line 192: "human resources were affected in four countries (Kyrgystan, Nigeria, and Viet Nam)").The tables are also mis-numbered (the tables are not numbered sequentially, and there are two Table 5s).Apologies for these errors, we have carefully copy-edited the manuscript and corrected the table-numbering.
4. There are also some data placeholders in the text still that need to be filled in (eg in supplement 3, for each of the four countries: "the first COVID-19 patient was notified in the XX database [REF]").Apologies for these errors, we have carefully copy-edited the manuscript and filled in or removed the placeholders.

Minor:
5. There are a number of abbreviations (eg "M&E") which may not be familiar to all readers; it would be helpful to use the full name instead.We have included description of acronyms in the tables.
6.The authors should briefly define "notification" in the methods section; this term is commonly used in the TB field but may not be familiar to the general reader.Similarly, I recommend the authors include a link to the website of the Global TB Program (as a reference) to aid those unfamiliar with it.Thank you for this suggestion.We have included an explanation of TB notification data and included a reference to the website of the Global TB Program.Methods: Major: 7.There is a lot of information presented, both qualitative and quantitative; not all of it is directly relevant to the main study objective.While COVID case data provides some context, there is no analysis of COVID case counts in relation to the main topic of TB notifications and TB program functioning.I recommend deleting the COVID case count data from the main manuscript.I think it just distracts from the authors' main focus, especially because COVID case data has all kinds of data completeness issues.It is interesting to include for context in the supplementary material though (supplement 3).Thank you for this suggestion.After thorough review of the manuscript and taking into account comments from all three reviewers, we followed your suggestion and excluded the data on COVID from the main manuscript and moved the data collection description to Supplement 3.
8. Similarly, data on TB treatment initiations and completions are included for 3/4 countries studied, but there is minimal analysis or comment on this aspect.I recommend deleting it from the main text and Figure 1, especially as it's not available for all of the countries.It is interesting to include in the supplemental data though.Thank you for this suggestion.After thorough review of the manuscript and taking into account comments from all three reviewers, we followed your suggestion and excluded the TB treatment data from the main manuscript and moved the data collection description to Supplement.
Minor: 9. the authors need to clarify the relationship between the "country profiles" in supplement #3 and the "landscape assessment" in supplement #1.I think the narrative, qualitative country profiles were the actual data collected by the KPNV country representative, and then this narrative, qualitative data was extracted into the more structured categorical landscape format to enable tabular and qualitative analysis.However this is not at all clear currently in the methods.To clarify the supplement 3, we added the following sentence to the methods section: "S3 Thank you for your suggestions to improve readability of Figure 1.We try to avoid using colors to accommodate persons who are colorblind.We changed the numbers of the IPC measures into letters.We also added the quarterly periods in the legend behind the IPC measures.
It is very confusing that some data beyond the study period are shown -eg TB notifications for Tanzania and Viet Nam continue past Q1 2021, and all COVID interventions in all countries appear to end suddenly at Q1 2021 despite other COVID data continuing past this time point.I strongly recommend the authors use a consistent end point for all data throughout the study -presumably this would be Q1 2021.We have updated the data until Q4 2021.
Minor: 12. Tables 3, 4, and 5 on TB program experiences and strategies are very helpful to organize and visualize this complex set of information.I recommend deleting Table 2, as I found Figure 1 much more useful to portray the same information on COVID intervention timelines in the 4 countries.All the tables should be re-numbered so they are in sequence, including the other "Table 5" on the correlation analysis (there are currently two table 5s) Thank you for your suggestion.We removed table 2 (table 1 after renumbering) from the manuscript.We apologize for the errors in numbering of the tables.We renumbered the tables accordingly.
13.The data on what aspects of TB programs were affected during the pandemic, and strategies used to strengthen services despite these challenges, are the most solid part of this study.This information is also very useful for other TB programs globally.I recommend the authors focus more on these components.Thank you for your suggestion.We have restructured the results section and envision this puts more focus to the topic of retaining and recovering TB care and prevention services.
Discussion: 14.The interpretation about correlation between COVID interventions and TB notifications needs to be strengthened.My interpretation is that the overall analysis did not show any clear correlation at all; correlation was strong for both Nigeria and Kyrgystan, but in opposite directions, and wasn't performed for Viet Nam for statistical reasons that I think may not be clear for many readers (defensible statistical choice, but not fully explained in the methods or results).Nevertheless, the question about impact of COVID measures on TB notifications is an urgent one to ask.It would be very useful for the authors to provide their interpretation / speculation on why this analysis was inconclusive/inconsistent. Thank you for this suggestion.We have added the following sentences to the discussion section: "To 15.Given that Nigeria was able to maintain gradual increase in TB notifications despite the pandemic, it would be very useful for the authors to include possible reasons why this apparent success happened, in contrast to the experience of the other 3 countries.
We added the following paragraph to the discussion section: "Our study showed increases in TB notifications for Nigeria.This is not in line with a study by Odume et al. (2020)

I
am not clear what the authors mean by "remote monitor and refill services" in line 222.Does this mean pharmacies delivering medications to the patient's home rather than the patient travelling to the pharmacy?These services can be executed in different ways, but are community-based.We adjusted the sentence into the following: "Furthermore, healthcare facilities in Nigeria limited the need for patients to travel to pharmacies by making more use of community-based treatment monitor and medication refill services."[Results section, Page 13, Lines[272][273][274]

Table 2 :
should this be labeled Table 2 when it's the first table in the paper?Is a table missing earlier?Otherwise, content is quite helpful.Please spell out acronyms in table legend.Apologies for this error, we corrected the numbering of the tables.Furthermore, we have added the acronyms to the table legend.

Table 4 :
what do the dark squares indicate?Suggest instead writing 'yes' or 'no'.We adjusted the table accordingly.
The authors should clarify why they used multiple and different sources for TB notification data across the 4 countries and time frame of the study.Why not get quarterly data through the Global TB program for the full study period(2018)(2019)(2020)(2021)for all 4 countries, so there would be more consistency?I can think of potential reasons, but there are none provided currently.We have added the data collection procedures and reasons for collecting data from different sources:First, we collected data publicly available data from the Global Tuberculosis Program (e.g.period Q1 2020 until Q4 2021 for all countries).Second, as quarterly data was not publicly available through the Global TB Program for the period prior to Q1 2020, we designed a data entry tool in Excel and approached KNCV's TB representatives to collect those data from the NTPs.For Viet Nam, quarterly data could not be obtained from the NTP for the period Q1 2018-Q1 2020) after which we collected publicly available annual data from the Global Tuberculosis Program and calculated average quarterly numbers by dividing annual TB notification numbers by four [Methods section, Page 7, Lines 132-139] Figure1presents the fundamental quantitative data in this study.The visuals are confusing -I recommend the authors revise the graphics/labelling for the intervention periods (ie when each intervention stopped and started) as this is currently difficult to interpret particularly for Kyrgystan.Using a different coloured horizontal bar (or thick line) for each type of intervention might work better.
assess the impact of COVID-19 IPC measures on TB notifications, future research is needed that take into account those factors and their magnitudes.Furthermore, future research should explore and take into account any programmatic and project interventions aimed at increasing TB notifications that were implemented simultaneously with the page 18, , who evaluated two active case finding interventions and showed a decrease in clinic attendance, presumptive TB identification, TB cases detected and TB treatment initiation during the first quarter of the COVID-19 pandemic.These findings were supported by Adwole (2020), who also showed reductions of 35% in presumptive TB and 34% in active TB cases detected in a health facility during the same period.News reports confirm the increase in TB notifications, which were contributed to programmatic and facilitybased interventions and integration of TB and COVID-19 measures Lacking scientific evidence, it is unclear to what extend new and additional efforts may have outweighed or masked the effects of COVID-19 on the TB epidemiology in Nigeria."[Discussionsection, page 17,